Salary for Mid-level / Intermediate Applied Scientist in Canada during 2024

Salary details

The average mid-level / intermediate Applied Scientist salary lies between USD 127,200 and USD 159,600 in Canada. It represents the overall compensation/gross salary amount for the working year (before deductions like social security, taxes and other contributions), not including equity/stock options or similar benefits.

Region represents the primary country of residence of an employee during the year (or residence for tax purposes). All data shown are full-time equivalent (FTE) salaries. Part-time salary information has been extrapolated to its FTE value.

Last updated: Dec. 15, 2024

Top 20 Job Tags for Mid-level / Intermediate Applied Scientist roles

The three most common job tag items assiciated with mid-level / intermediate Applied Scientist job listings are Machine Learning, Python and PhD. Below you find a list of the 20 most occuring job tags in 2024 and the number of open jobs that where associated with them during that period:

Machine Learning | 174 jobs Python | 158 jobs PhD | 146 jobs Research | 136 jobs Java | 132 jobs Deep Learning | 99 jobs Engineering | 94 jobs Data Mining | 92 jobs LLMs | 83 jobs Computer Science | 79 jobs ML models | 71 jobs Linux | 69 jobs Statistics | 65 jobs NLP | 62 jobs Generative AI | 59 jobs PyTorch | 51 jobs TensorFlow | 45 jobs Security | 40 jobs AWS | 39 jobs CX | 39 jobs

Top 20 Job Perks/Benefits for Mid-level / Intermediate Applied Scientist roles

The three most common job benefits and perks assiciated with mid-level / intermediate Applied Scientist job listings are Career development, Conferences and Equity / stock options. Below you find a list of the 20 most occuring job perks or benefits in 2024 and the number of open jobs that where offering them during that period:

Career development | 161 jobs Conferences | 107 jobs Equity / stock options | 102 jobs Startup environment | 44 jobs Medical leave | 37 jobs Health care | 30 jobs Team events | 30 jobs Flex hours | 19 jobs Parental leave | 13 jobs Flex vacation | 6 jobs Insurance | 6 jobs Relocation support | 5 jobs Competitive pay | 4 jobs Salary bonus | 4 jobs Home office stipend | 4 jobs 401(k) matching | 3 jobs Flexible spending account | 3 jobs Wellness | 1 jobs Gear | 1 jobs Fitness / gym | 1 jobs

Salary Composition

In Canada, the salary composition for a mid-level/intermediate applied scientist in AI/ML/Data Science typically includes a base salary, performance bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The base salary is the fixed component and usually constitutes the majority of the total compensation package. Performance bonuses can vary significantly depending on the company’s policy and individual performance, often ranging from 10% to 20% of the base salary. Additional remuneration might include benefits like health insurance, retirement contributions, and sometimes relocation assistance. The exact composition can vary based on the region, with tech hubs like Toronto and Vancouver potentially offering higher base salaries and bonuses. Industry and company size also play a role; larger tech companies or those in high-demand sectors may offer more competitive packages, including significant equity components.

Increasing Salary

To increase your salary from a mid-level position, consider the following strategies:

• Skill Enhancement: Continuously update and expand your technical skills, particularly in emerging AI/ML technologies and tools. Specializing in niche areas like deep learning, natural language processing, or computer vision can make you more valuable.

• Advanced Education: Pursuing further education, such as a Ph.D. or specialized certifications, can position you for higher-level roles and salary brackets.

• Leadership Roles: Transitioning into leadership or managerial roles can significantly boost your earning potential. This might involve leading projects, managing teams, or taking on more strategic responsibilities.

• Networking and Industry Engagement: Actively participating in industry conferences, workshops, and networking events can open up opportunities for higher-paying roles and collaborations.

• Negotiation Skills: Improving your negotiation skills can help you secure better compensation packages when changing jobs or during performance reviews.

Educational Requirements

Most mid-level applied scientist roles in AI/ML/Data Science require at least a master’s degree in a relevant field such as computer science, data science, statistics, or engineering. A strong foundation in mathematics and statistics is crucial, as is proficiency in programming languages like Python or R. Some positions may also consider candidates with a bachelor’s degree if they have significant relevant experience or exceptional skills.

Helpful Certifications

While not always mandatory, certain certifications can enhance your profile and demonstrate your expertise:

• Certified Machine Learning Professional (CMLP)
• TensorFlow Developer Certificate
• AWS Certified Machine Learning – Specialty
• Microsoft Certified: Azure AI Engineer Associate

These certifications can validate your skills in specific tools and platforms, making you more attractive to potential employers.

Required Experience

Typically, a mid-level applied scientist role requires 3-5 years of experience in the field. This experience should include hands-on work with machine learning models, data analysis, and software development. Experience in deploying models to production and working in cross-functional teams is often highly valued. Additionally, experience in a specific industry, such as finance, healthcare, or technology, can be advantageous.

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